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AI Engineer with 1+ years in Data Science & Machine Learning
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Assessing your cultural and operational fit
Motivated Computer Science graduate with hands-on experience in AI/ML, Python, SQL, Power BI, and Microsoft Power Platform. Completed internships involving machine learning, data analysis, and application development. Passionate about building scalable software solutions and eager to contribute as a Software Developer while continuously learning new technologies.
APJ Abdul Kalam Technological University
Bachelor of Technology · Computer Science and Engineering
August 1, 2021 – April 1, 2025
Exult Global
AI & Automation Intern
April 1, 2026 – Present
Cochin, Kerala, India
Luminar Technolab
Data Science Intern
May 1, 2025 – February 1, 2026
Cochin, Kerala, India
Infrastructure Solutions Group, Dell Technologies
Internship Experience
January 1, 2024 – January 1, 2025
India
OCR-Enabled RAG Chatbot
June 26, 2026 – Present
Designed and implemented a Retrieval-Augmented Generation (RAG) system for document-based question answering using Lang Chain, FAISS, and Hugging Face Transformers. Built an OCR-enabled data ingestion pipeline to process both text and scanned PDFs, converting unstructured documents into searchable vector embeddings. NLP techniques such as text chunking, semantic embeddings, and similarity search to improve document retrieval accuracy. Developed a Streamlit-based interactive chatbot.
AI Public Speaking & Interview Coach
June 26, 2026 – Present
Developed an AI-powered public speaking and interview coach using computer vision to evaluate speaker confidence in real time. Analyzed eye contact, blink rate, head movement, and body posture using facial landmark and pose estimation techniques. Designed a confidence scoring mechanism by aggregating multiple behavioral cues related to gaze stability and posture alignment. Built an interactive Streamlit dashboard to provide live feedback and actionable insights for interview and presentation improvement.
MoodSense
June 26, 2026 – Present
Developed a platform for early detection of depression by analyzing user-input text for depressive patterns. Implemented a machine learning model to predict depression severity and generate a quantitative depression score. Enabled early intervention support through data-driven insights derived from textual sentiment and behavioral analysis. Technologies used: HTML, CSS, Python, Flask, TensorFlow, Keras, Anaconda, and Jupyter Notebook.
Cultural Fit Analysis
The candidate's project diversity, ranging from RAG chatbots to AI coaches and depression detection platforms, indicates a broad interest in applying ML to various real-world problems. Their involvement in volunteer roles (Secretary, Chairperson for IEEE student branches) suggests a collaborative spirit and leadership potential. The internships, particularly the one at Dell Technologies focusing on sustainable mobility, show an interest in impactful and environmentally conscious solutions, which could align with a company valuing social responsibility. The candidate's continuous learning and application of new technologies also suggest a good fit for an innovative and growth-oriented culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving, self-learning, and adaptability skills through their diverse personal projects and internship experiences. Their involvement in volunteer activities also suggests leadership and event management capabilities, which are beneficial for team collaboration and project execution. The candidate's profile indicates a proactive approach to learning and applying new technologies, aligning well with the dynamic nature of an ML Engineer role.